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As customer requirements change more frequently, pursuing flexible and adaptive automation approaches becomes necessary. Such approaches demand an explicit description of a production system's functionality and the products to be manufactured. Recent research has introduced approaches based on capabilities and skills using holistic data models (i.e., ontologies, DSLs, variability models ...). While capabilities are understood as an abstract description of (manufacturing) processes a system can perform, skills are often described as their executable counterparts (i.e., modelling an invocation interface such as OPC UA). To find solutions for customer requirements automatically, required tasks and domain-specific constraints must be matched with capabilities provided by automation components. This can be achieved by various techniques such as AI planning or knowledge graph exploration and reasoning. Process plans can then be orchestrated by combining skills related to capabilities found in the previous step. Finally, simulation and optimization of such process plans can be performed before executing them.